We study 2D keypoint detection baselines on HuMMan primarily for 2D-to-3D keypoint lifting. CPN [1]} is a cascaded pyramid network to improve hard keypoints detection. HRNet [2]} is a novel high-resolution network that obtains high performance on COCO dataset [3]}, and LiteHRNet is an efficient version of HRNet. The comparison results are listed in Table  REF . Because 2D keypoints are often used as an intermediate representation of 3D keypoints in a two-stage manner [4]}, [5]}, the good performance in this task can be helpful to the estimation of subsequent 3D.
